[HTML][HTML] ERS/ATS technical standard on interpretive strategies for routine lung function tests

S Stanojevic, DA Kaminsky, MR Miller… - European …, 2022‏ - publications.ersnet.org
Background Appropriate interpretation of pulmonary function tests (PFTs) involves the
classification of observed values as within/outside the normal range based on a reference …

Treatment trials in young patients with chronic obstructive pulmonary disease and pre–chronic obstructive pulmonary disease patients: time to move forward

FJ Martinez, A Agusti, BR Celli, MLK Han… - American journal of …, 2022‏ - atsjournals.org
Chronic obstructive pulmonary disease (COPD) is the end result of a series of dynamic and
cumulative gene–environment interactions over a lifetime. The evolving understanding of …

Artificial intelligence and machine learning in chronic airway diseases: focus on asthma and chronic obstructive pulmonary disease

Y Feng, Y Wang, C Zeng, H Mao - International journal of …, 2021‏ - pmc.ncbi.nlm.nih.gov
Chronic airway diseases are characterized by airway inflammation, obstruction, and
remodeling and show high prevalence, especially in develo** countries. Among them …

Deep learning–based approach to predict pulmonary function at chest CT

H Park, J Yun, SM Lee, HJ Hwang, JB Seo, YJ Jung… - Radiology, 2023‏ - pubs.rsna.org
Background Low-dose chest CT screening is recommended for smokers with the potential
for lung function abnormality, but its role in predicting lung function remains unclear …

Fx-Net and PureNet: Convolutional Neural Network architecture for discrimination of Chronic Obstructive Pulmonary Disease from smokers and healthy subjects …

C Avian, MI Mahali, NAS Putro, SW Prakosa… - Computers in Biology …, 2022‏ - Elsevier
As one of the most reliable and significant indicators, Chronic Obstructive Pulmonary
Disease (COPD) becomes a robust predictor of lung cancer early detection, the world's …

Deep learning parametric response map** from inspiratory chest CT scans: a new approach for small airway disease screening

B Chen, Z Liu, J Lu, Z Li, K Kuang, J Yang, Z Wang… - Respiratory …, 2023‏ - Springer
Objectives Parametric response map** (PRM) enables the evaluation of small airway
disease (SAD) at the voxel level, but requires both inspiratory and expiratory chest CT …

Analyzing the use of artificial intelligence for the management of chronic obstructive pulmonary disease (COPD)

ADR Fernández, DR Fernández, VG Iglesias… - International journal of …, 2022‏ - Elsevier
Objective Chronic obstructive pulmonary disease (COPD) is a disease that causes airflow
limitation to the lungs and has a high morbidity around the world. The objective of this study …

Application of machine learning in pulmonary function assessment where are we now and where are we going?

PC Giri, AM Chowdhury, A Bedoya, H Chen… - Frontiers in …, 2021‏ - frontiersin.org
Analysis of pulmonary function tests (PFTs) is an area where machine learning (ML) may
benefit clinicians, researchers, and the patients. PFT measures spirometry, lung volumes …

SmoothHess: ReLU network feature interactions via stein's lemma

M Torop, A Masoomi, D Hill, K Kose… - Advances in Neural …, 2023‏ - proceedings.neurips.cc
Several recent methods for interpretability model feature interactions by looking at the
Hessian of a neural network. This poses a challenge for ReLU networks, which are …

Aritificial Inteligence Challenges in COPD management: a review

LS Bećirović, A Deumić, LG Pokvić… - 2021 IEEE 21st …, 2021‏ - ieeexplore.ieee.org
Machine learning algorithms have been drawing attention in lung disease research.
However, due to their algorithmic learning complexity and the variability of their architecture …